LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models
This addresses the challenge of automatic visualization generation for users in data analysis and presentation, though it is incremental as it builds on existing LLM and IGM technologies.
The authors tackled the problem of automating visualization creation by developing LIDA, a tool that uses large language models and image generation models to generate grammar-agnostic visualizations and infographics, resulting in a system with modules for data summarization, goal exploration, code generation, and stylized graphics production.
Systems that support users in the automatic creation of visualizations must address several subtasks - understand the semantics of data, enumerate relevant visualization goals and generate visualization specifications. In this work, we pose visualization generation as a multi-stage generation problem and argue that well-orchestrated pipelines based on large language models (LLMs) such as ChatGPT/GPT-4 and image generation models (IGMs) are suitable to addressing these tasks. We present LIDA, a novel tool for generating grammar-agnostic visualizations and infographics. LIDA comprises of 4 modules - A SUMMARIZER that converts data into a rich but compact natural language summary, a GOAL EXPLORER that enumerates visualization goals given the data, a VISGENERATOR that generates, refines, executes and filters visualization code and an INFOGRAPHER module that yields data-faithful stylized graphics using IGMs. LIDA provides a python api, and a hybrid user interface (direct manipulation and multilingual natural language) for interactive chart, infographics and data story generation. Learn more about the project here - https://microsoft.github.io/lida/